Whether to pay a managed service to run your AI agents or hire someone to build and run them on staff.
A full-time AI or software engineer brings deep context and is always on hand, at a salary near or above the software developer median. A managed agent plan costs less than one hire at small scale and goes live faster, but you depend on an outside team. This page compares the two on time to go live, ongoing work, cost, data and risk.
Quick answer
A managed plan is usually cheaper and faster when you run up to about fifteen agents and do not have full-time engineering work. Our plans are $4,000, $7,600 or $15,600 a month. Hire when AI is core to your product and you have steady work for a full-time engineer, which BLS data puts at a $135,980 median wage before benefits.
Deciding between a managed plan and a hire?
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At a glance
Managed AI Agents
In-House Hire
| Dimension | Managed AI Agents | In-House Hire | Verdict |
|---|---|---|---|
| Time to go live | Weeks: setup covers mapping, connections, testing and handover | Months: recruiting and onboarding come before the first agent is built | Managed is faster to the first working agent. A hire pays off over a longer horizon. |
| Cost | OrchestriAI plans run $4,000, $7,600 or $15,600 a month plus setup from $3,000; other managed services start around $5,000 a month | BLS puts the May 2025 median software developer wage at $135,980 a year; AI specialists, benefits and taxes push the total to $150,000 or more | At one to fifteen agents, a managed plan usually costs less than one loaded salary. At larger scale, the math can flip. |
| Ongoing management | The provider monitors runs, fixes failures and updates agents when vendors change | Your hire does all of it, and covers holidays, sick days and turnover planning | A single hire is a single point of failure. A managed plan spreads that risk, at the cost of control. |
| Business context | Learned during setup and kept in documentation | Builds every day the person sits in your business | A good hire learns your business more deeply over time. Write the context down either way. |
| Data privacy | Agents run in your accounts with scoped access; the provider should sign the agreements your data needs | Access stays inside your company, under your own policies | Both can be done safely. Check access scopes, agreements and offboarding steps before choosing either. |
| Ownership | You should own the code, accounts and prompts; check the contract for export terms | Everything is owned by the company from day one | Insist on ownership and a clean exit with a managed provider. It removes most lock-in risk. |
When a managed platform is enough, and when your workflow needs owned code and infrastructure.
Both add operational capacity, but their judgment, supervision, and cost structures are different.
MCP commonly uses existing APIs; it adds a standard interface for compatible AI applications.
Deployment control matters, but no workflow platform is HIPAA-compliant by configuration alone.
Whether to hire a firm or an independent freelancer to build your automations and AI agents.
Three self-hosted agent platforms with different centers: a chat assistant, an agent runtime, and a team workspace.
What each one charges for, where your data runs, and when owned code is worth the upfront cost.
Free. Three fields. We reply within one business day.
Tell us the work you need covered and we'll give you an honest view of which fits.
What happens next
“Shariq built our Open Dental to GoHighLevel sync and our AI routing system for new patient inquiries. Both projects were delivered fast, worked right away, and he was responsive whenever we needed adjustments. He understands dental practice workflows and doesn't overcomplicate things.”
Talk to Shariq
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